Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological
Administration, Collaborative Innovation Center on Forecast and Evaluation
of Meteorological Disasters, School of Atmospheric Physics, Nanjing
University of Information Science and Technology, Nanjing 210044, China
John A. Paulson School of Engineering and Applied Sciences, Harvard
University, Cambridge, Massachusetts 02138, USA
Daniel J. Jacob
John A. Paulson School of Engineering and Applied Sciences, Harvard
University, Cambridge, Massachusetts 02138, USA
Key Laboratory for Atmospheric Chemistry, Chinese Academy of
Meteorological Sciences, CMA, Beijing 100081, China
Tianliang Zhao
Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological
Administration, Collaborative Innovation Center on Forecast and Evaluation
of Meteorological Disasters, School of Atmospheric Physics, Nanjing
University of Information Science and Technology, Nanjing 210044, China
Hong Liao
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, School of Environmental Science and
Engineering, Nanjing University of Information Science and Technology,
Nanjing 210044, China
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13,236
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17,792
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Cumulative views and downloads
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Total article views: 16,103 (including HTML, PDF, and XML)
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12,507
3,473
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16,103
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383
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PDF: 3,473
XML: 123
Total: 16,103
Supplement: 624
BibTeX: 182
EndNote: 383
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Cumulative views and downloads
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Total article views: 1,689 (including HTML, PDF, and XML)
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729
941
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1,689
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31
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Total: 1,689
Supplement: 190
BibTeX: 19
EndNote: 31
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Viewed (geographical distribution)
Total article views: 17,792 (including HTML, PDF, and XML)
Thereof 17,384 with geography defined
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Total article views: 16,103 (including HTML, PDF, and XML)
Thereof 15,881 with geography defined
and 222 with unknown origin.
Total article views: 1,689 (including HTML, PDF, and XML)
Thereof 1,503 with geography defined
and 186 with unknown origin.
Observed annual mean PM2.5 decreased by 30–50 % in China from 2013–2018. However, meteorologically PM2.5 variability complicates trend attribution. We used a stepwise multiple linear regression model to quantitatively separate contributions from anthropogenic emissions and meteorology. Results show that 88 % of the PM2.5 decrease across China is attributable to anthropogenic emission changes, and 12 % is attributable to meteorology.
Observed annual mean PM2.5 decreased by 30–50 % in China from 2013–2018. However,...
